ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 2 No. 1-2 (2017): TTTP - APEIRON

Marko Subotić, Milan Tešić, Nikica Vidović

Analysis of the level of satisfaction of road network users - case review of road section Koprivna – Modriča (r-465)

Original scientific paper

DOI: 10.7251/JTTTP1701034S

Abstract

The paper conducts a survey of satisfaction level of users of two lane road in regards to con- structional-geometrical factors influencing unimpeded traffic and influence of human element during its maintenance. Establishing the satisfaction level of users of existing road network is the primary goal of the paper, through the definition of Level of Service of relevance for the analysis of traffic of inter- urban road network. The survey was conducted on the road section Koprivna – Modriča, regional road R-465 (Bušletić- Modriča). Using a questionnaire, the values of influence to the level of users’ satisfac- tion were established. Traffic infrastructure and elements of horizontal road signs have been identified as two main indicators giving negative grade to the level of satisfaction. The end of paper gives a review of measures for the improvement of existing conditions.

Keywords : Level of Service (LOS), road network, road section.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.